When you create a model, PerceptiLabs automatically creates and adds both an Input (1) and a Target (2) Component to your model:
The Input Component (1) represents the input data for your model and points to the .csv file you specified when you created the model. It provides a visualization using the first sample from your input data.
The TargetComponent (2) provides a visualization of the labels / the result we want the model to achieve (e.g., classification).
The screenshot above shows a basic image classification model, where the Input's visualization displays the first image of the input data while the Target's visualization shows the (normalized) probability for the classification of that image.